DRF

Supported HTTP methods and descriptions

URL

http://<h2oHost>:<h2oApiPort>/DRF.json

Input parameters

  • classification, a boolean, <i>expert</i>

    Do classification or regression. Since version 1

  • validation, a Frame, <i>expert</i>

    Validation frame. Since version 1

  • n_folds, a int, <i>expert</i>

    Number of folds for cross-validation (if no validation data is specified). Since version 1

  • keep_cross_validation_splits, a boolean, <i>expert</i>

    Keep cross-validation dataset splits. Since version 1

  • ntrees, a int, <i>critical</i>

    Number of trees. Since version 1

  • max_depth, a int, <i>critical</i>

    Maximum tree depth. Since version 1

  • min_rows, a int, <i>secondary</i>

    Fewest allowed observations in a leaf (in R called ‘nodesize’). Since version 1

  • nbins, a int, <i>secondary</i>

    Build a histogram of this many bins, then split at the best point. Since version 1

  • score_each_iteration, a boolean, <i>expert</i>

    Perform scoring after each iteration (can be slow). Since version 1

  • importance, a boolean, <i>expert</i>

    Compute variable importance (true/false).. Since version 1

  • balance_classes, a boolean, <i>expert</i>

    Balance training data class counts via over/under-sampling (for imbalanced data). Since version 1

  • max_after_balance_size, a float, <i>expert</i>

    Maximum relative size of the training data after balancing class counts (can be less than 1.0). Since version 1

  • checkpoint, a Key, <i>expert</i>

    Model checkpoint to start building a new model from. Since version 1

  • overwrite_checkpoint, a boolean, <i>expert</i>

    Overwrite checkpoint. Since version 1

  • mtries, a int, <i>expert</i>

    Columns to randomly select at each level, or -1 for sqrt(#cols). Since version 1

  • sample_rate, a float, <i>secondary</i>

    Sample rate, from 0. to 1.0. Since version 1

  • seed, a long, <i>expert</i>

    Seed for the random number generator (autogenerated). Since version 1

  • do_grpsplit, a boolean, <i>expert</i>

    Check non-contiguous group splits for categorical predictors. Since version 1

  • build_tree_one_node, a boolean, <i>secondary</i>

    Run on one node only; no network overhead but fewer cpus used. Suitable for small datasets.. Since version 1

Output JSON elements

  • xval_models, a Key[]

    Cross-validation models. Since version 1, expert

  • _distribution, a long[]

    Class distribution. Since version 1, expert

  • _mtry, a int

    Computed number of split features. Since version 1, expert

  • _seed, a long

    Autogenerated seed. Since version 1, expert

HTTP response codes

200 OK Success and error responses are identical.